Remote data monitoring for anomalous behavior, such as remote monitoring of seismic sensors, volcanic sensors, oil or gas wells, weather stations, ocean buoys and the like, poses data communication challenges, particularly when the monitored item is located far from telecommunications infrastructure or regular sources of electric power. For example, remote monitoring of ambulatory patients enables doctors to detect or diagnose heart problems, such as arrhythmias, that may produce only transient symptoms and, therefore, may not be evident when the patients visit the doctors' offices. Several forms of cardiac event monitors have been used.
A “Holter” monitor is worn by a patient and collects and stores data for a period of time, typically at least 24 hours, and in some cases up to two weeks. After the data has been collected, the Holter monitor is typically brought or sent to a doctor's office, laboratory or the like, and the data is retrieved from the monitor and analyzed. Holter monitors are relatively inexpensive, but they cannot be used for real-time analysis of patient data, because the data is analyzed hours, days or weeks after it has been collected.
More timely analysis of heart data is made possible by pre-symptom (looping memory) event monitors. Such a device collects and stores patient data in a “loop” memory device. The event monitor constantly overwrites previously stored data with newly collected data. The event monitor may include a button, which the patient is instructed to actuate if the patient feels ill or otherwise detects a heart-related anomaly. In response, the event monitor continues to record data for a short period of time and then stops recording, thereby retaining data for a time period that spans the button actuation, i.e., the retained data represents a period of time that extends from (typically) a few minutes before the user actuated the button to (typically) a few minutes after the user actuated the button. The retained data may then be sent via a modem and a telephone connection to a doctor's office or to a laboratory for analysis. Although such an event monitor can facilitate analysis of patient data more proximate in time to the patient-detected anomaly, relying on the patient to actuate the device and then send the data can be problematic.
Some event monitors automatically detect certain arrhythmias and, in response, record electrocardiograph (ECG) data. Automatic event monitors are thought to be more sensitive, but less specific, than manually triggered cardiac event monitors for significant cardiac arrhythmias. However, these devices still rely on patients to send the recorded data for analysis, and there is still a delay between detection of a suspected arrhythmia and transmission of the data.
Mobile cardiovascular telemetry (MCT) refers to a technique that involves noninvasive ambulatory cardiac event monitors that are capable of continuous measurements of heart rate and rhythm over several days. For example, CardioNet, Philadelphia, Pa., provides an MCT device under the trade name “Mobile Cardiac Outpatient Telemetry” (MCOT). The MCOT device includes an automatic ECG arrhythmia detector. The MCOT device couples to a cellular telephone device to immediately transmit automatically detected abnormal ECG waveforms to a remote monitoring center, which can then alert a physician. The MCOT device also includes a memory capable of storing up to 96 hours of ECG waveform data, which can be transmitted over standard telephone lines to the remote monitoring center at the end of each day. Although data about automatically detected arrhythmias are sent immediately to the remote monitoring center, without requiring patient action, the computational resources and corresponding electrical power (battery) required to perform the automatic ECG analysis in the MCOT device are significant.
Some MCT devices continuously send all collected ECG data to a remote monitoring center for analysis. These MCT devices typically do not perform any ECG analysis of their own. Although no patient-initiated action is required, the large amount of data transmitted by the MCT wireless devices congests the wireless channels used to convey the data. Furthermore, a large amount of computational resources is required at the remote monitoring center to analyze the continuous stream of received data, especially when many patients are monitored by a single data center.
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